{"id":"https://openalex.org/W7165028866","doi":"https://doi.org/10.48550/arxiv.2606.17591","title":"Closing the Feedback Loop: From Experience Extraction to Insight Governance in Verbal Reinforcement Learning","display_name":"Closing the Feedback Loop: From Experience Extraction to Insight Governance in Verbal Reinforcement Learning","publication_year":2026,"publication_date":"2026-06-16","ids":{"openalex":"https://openalex.org/W7165028866","doi":"https://doi.org/10.48550/arxiv.2606.17591"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.17591","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.17591","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.17591","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063371086","display_name":"Yanwei Cui","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cui, Yanwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138788149","display_name":"Xing Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138828474","display_name":"Yulong Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yulong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138808312","display_name":"Li Shao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shao, Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138777000","display_name":"Xiaofeng Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Xiaofeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138762425","display_name":"Guanghui Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Guanghui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138776467","display_name":"Peiyang He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Peiyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.20409999787807465,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.20409999787807465,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11883","display_name":"Embodied and Extended Cognition","score":0.1298000067472458,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.05790000036358833,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.7055000066757202},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6862000226974487},{"id":"https://openalex.org/keywords/closing","display_name":"Closing (real estate)","score":0.6351000070571899},{"id":"https://openalex.org/keywords/dilemma","display_name":"Dilemma","score":0.5667999982833862},{"id":"https://openalex.org/keywords/corporate-governance","display_name":"Corporate governance","score":0.5299000144004822},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5178999900817871},{"id":"https://openalex.org/keywords/feedback-loop","display_name":"Feedback loop","score":0.49630001187324524},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.46860000491142273}],"concepts":[{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.7055000066757202},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6862000226974487},{"id":"https://openalex.org/C2778775528","wikidata":"https://www.wikidata.org/wiki/Q5135432","display_name":"Closing (real estate)","level":2,"score":0.6351000070571899},{"id":"https://openalex.org/C2778496695","wikidata":"https://www.wikidata.org/wiki/Q254128","display_name":"Dilemma","level":2,"score":0.5667999982833862},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5442000031471252},{"id":"https://openalex.org/C39389867","wikidata":"https://www.wikidata.org/wiki/Q380767","display_name":"Corporate governance","level":2,"score":0.5299000144004822},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5178999900817871},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5001000165939331},{"id":"https://openalex.org/C186886427","wikidata":"https://www.wikidata.org/wiki/Q5441213","display_name":"Feedback loop","level":2,"score":0.49630001187324524},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.46860000491142273},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3610000014305115},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.34940001368522644},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.336899995803833},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.334199994802475},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3255000114440918},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.31040000915527344},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.2976999878883362},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.29109999537467957},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C195094911","wikidata":"https://www.wikidata.org/wiki/Q14167904","display_name":"Process management","level":1,"score":0.28630000352859497},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.2822999954223633},{"id":"https://openalex.org/C2778137410","wikidata":"https://www.wikidata.org/wiki/Q2732820","display_name":"Government (linguistics)","level":2,"score":0.2750999927520752},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.27459999918937683},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.2718000113964081},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.27149999141693115}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.17591","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.17591","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.17591","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.17591","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Training-free":[0],"verbal":[1,28],"reinforcement":[2],"learning":[3],"enables":[4],"LLM":[5],"agents":[6,49],"to":[7,146,149,154],"learn":[8],"from":[9,30,131],"world":[10,132,164],"feedback":[11,165],"--":[12,25,77,89,110,115],"objective":[13],"signals":[14],"such":[15],"as":[16,35,159],"dynamic":[17],"task":[18],"outcomes,":[19],"market":[20],"returns,":[21,192],"or":[22,186],"demand":[23],"forecasts":[24],"by":[26,117],"extracting":[27],"rules":[29,145],"experience":[31,98,130,178],"and":[32,86,90,113,152,170,190],"injecting":[33],"them":[34,62],"context,":[36],"updating":[37],"the":[38,124,175,183,196],"agent's":[39],"behavior":[40],"without":[41],"parameter":[42],"changes.":[43],"However,":[44],"in":[45,97,102],"non-stationary":[46],"environments":[47],"these":[48],"face":[50],"a":[51,107,118,160],"retention-forgetting":[52],"dilemma:":[53],"retaining":[54],"stale":[55],"insights":[56],"causes":[57,63],"negative":[58],"transfer,":[59],"while":[60,100],"discarding":[61],"catastrophic":[64],"forgetting":[65],"when":[66,153],"conditions":[67],"recur.":[68],"We":[69,105],"identify":[70],"four":[71],"requirements":[72],"for":[73],"navigating":[74],"this":[75],"dilemma":[76],"outcome-driven":[78],"evaluation,":[79],"persistent":[80],"structured":[81],"evidence,":[82,112],"non-monotonic":[83],"knowledge":[84],"lifecycle,":[85],"compositional":[87],"governance":[88,125],"show":[91,173],"that":[92,122,174],"existing":[93],"methods":[94],"invest":[95],"heavily":[96],"extraction":[99],"underinvesting":[101],"insight":[103],"governance.":[104],"propose":[106],"three-layer":[108],"architecture":[109],"rules,":[111],"skills":[114,142],"connected":[116],"feedback-driven":[119],"curation":[120,197],"loop":[121,198],"closes":[123],"gap.":[126],"Rules":[127],"capture":[128],"distilled":[129],"outcomes;":[133],"evidence":[134],"logs":[135],"track":[136],"each":[137],"rule's":[138],"reliability":[139],"across":[140],"episodes;":[141],"govern":[143],"which":[144],"apply,":[147],"how":[148],"resolve":[150],"conflicts,":[151],"abstain.":[155],"On":[156],"financial":[157],"forecasting":[158],"case":[161],"study,":[162],"where":[163],"is":[166,199],"naturally":[167],"abundant,":[168],"noisy,":[169],"non-stationary,":[171],"we":[172],"same":[176],"accumulated":[177],"either":[179],"degrades":[180],"performance":[181],"below":[182],"zero-shot":[184],"baseline":[185],"dramatically":[187],"improves":[188],"accuracy":[189],"risk-adjusted":[191],"depending":[193],"on":[194],"whether":[195],"present.":[200]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-18T00:00:00"}